Jouni Nousiainen

Prediction of the relative intake potential of grass silage by dairy cows

Data based on the mean treatment values from production studies in lactating dairy cows were used to estimate relationships between silage composition and silage dry matter intake (SDMI). Data from 21 studies were used to estimate relationships between D-value (g digestible organic matter in kg dry matter (DM)) and crude protein (CP) content, and SDMI. The silages were harvested at different maturities but using the same ensiling techniques within the study. Relationships between silage fermentation characteristics and SDMI were estimated using data from 47 studies. The silages were harvested at the same time from the same sward but using various additives. When factorial designs were used, silage data within each treatment (subexperiment) were recorded separately. The data sets included 125 D-value and 234 fermentation observations. Relationships between SDMI and silage parameters were analyzed using mixed model regression analyses with experiment as a fixed factor and subexperiment within experiment as a random factor. The ranges for silage CP concentration and D-value were 111 to 238 (S.D. 25.2) and 589 to 756 (S.D. 48.5) g/kg DM, respectively. D-value was a much better predictor of SDMI than CP (R2 within experiment 0.71 vs. 0.26). The effect of D-value on SDMI diminished with increasing level of concentrate supplementation (interaction P<0.001). D-value had a greater effect on SDMI when the total DM intake was high. SDMI was negatively correlated with concentrations of ammonia N, lactic acid, individual and total volatile fatty acids and total fermentation acids and positively correlated to the concentration of residual water soluble carbohydrates. Total acid concentration was the best SDMI predictor of individual fermentation parameters (R2 within experiment 0.41) followed by lactic acid and ammonia N. Use of quadratic regressions generally increased the variation accounted for by the model. The best multiple regression accounted for 0.51 of the variation in SDMI within experiment. To facilitate interpretation of data, a theoretical model is presented. An interplay between physical load and capacity to use energy determines SDMI of well-fermented silages over the whole range of D-values. With increasing extent of fermentation SDMI is constrained by nutrient imbalance, most probably amino acid to energy ratio at the tissue level, resulting from reduced microbial protein synthesis in the rumen. Low palatability can further constrain silage DM intake. For advisory silage evaluation the following model predicting relative SDMI is proposed: SDMI index=100+0.151×(D-value−690)−0.000531×(TA2−6400)−4.7650 [Ln(Ammonia N) −Ln(50)], where D-value and total acids (TA) are expressed as g/kg DM and ammonia N as g/kg total N, respectively. Regression coefficients are scaled to a mean SDMI of 10 kg DM/day. The values of 690, 80 and 50 are used as standard D-value (g/kg DM), total acid (g/kg DM) and ammonia N (g/kg N) for high quality restrictively fermented silages. The model parameters were limited to those which are currently available for Finnish farm silage analyses, i.e., by near infra-red reflectance spectra (D-value) and electrometric titration (fermentation parameters).

Prediction of the digestibility of the primary growth of grass silages harvested at different stages of maturity from chemical composition and pepsin-cellulase solubility

Abstract Relationships between silage chemical components or organic matter (OM) pepsin-cellulase solubility and in vivo organic matter digestibility (OMD) and D -value (digestible OM content in dry matter) were studied. Twenty-five silages were made from primary growth timothy-meadow fescue swards in 6 years (3–6 silages per year) at 6–10 days intervals. The silages were analyzed for chemical composition, in vitro pepsin-cellulase solubility and in vivo digestibility in sheep. Chemical components of silage were highly correlated with OMD and D -value, but the accuracy of the OMD and D -value prediction equations were not satisfactory for ration formulation. Acid detergent fibre was the best single predictor of chemical parameters explaining 0.80 of the variation in OMD (residual mean square error (RMSE) 27.2gkg −1 ). Relationships between crude protein (CP) and lignin were improved, when the effects of year or year × component interaction were included in the model. For CP the intercepts and for lignin the slopes, were different between the years. Pepsin-cellulase solubility was superior to chemical parameters in predicting silage OMD and D -value. The monovariate regression equation between OM solubility and OMD was: OMD (gkg−1)=97+0.87×OM solubility ( R 2 =0.974; RMSE=10.8gkg −1 ). Prediction of D -value was improved by including ash as a second factor in bivariate regression analysis: D -value (gDOM(kgDM)−1)=160+0.818×OM solubility −1.09×ash ( R 2 =0.974; RMSE=9.7gkg −1 ). It was concluded that OM pepsin-cellulase solubility has great potential in predicting silage OMD and D -value both precisely and accurately.

A meta-analysis of feed digestion in dairy cows. 2. The effects of feeding level and diet composition on digestibility.

A meta-analysis based on published experiments with lactating dairy cows fed mainly grass silage-based diets was conducted to study the effects of intake, diet composition, and digestibility at a maintenance level of feeding on the apparent total diet digestibility. A data set that included a total of 497 dietary treatment means from 92 studies was collected and analyzed using mixed model regression analysis with a random study effect. Diet organic matter digestibility (OMD) in dairy cows at a production level (OMD(p)) was positively associated with OMD at maintenance (OMD(m)), but the slope was less than 1 (0.69). Diet OMD(p) decreased as feed intake increased, and diets with high OMD(m) exhibited greater depressions in digestibility with increased intake than did diets with low OMD(m). Digestibility of organic matter and neutral detergent fiber (NDF) increased as dietary crude protein concentration increased, whereas increased concentrate fat decreased digestibility. Replacement of grass silage with whole-crop cereal silage was associated with a quadratic decrease in diet digestibility. Metabolic fecal output, defined as fecal organic matter minus NDF, averaged 95.8 (SE = 0.65) g/kg of dry matter intake, and it was not influenced by intake or diet composition. Variation in OMD(p) in cows fed grass silage-based diets was therefore attributable to variation in dietary NDF concentration and NDF digestibility. Depression in digestibility of organic matter with increased intake was less than predicted by the National Research Council and Cornell Net Carbohydrate and Protein systems. The following 2-parameter model indicates that the difference between OMD estimated in sheep fed at maintenance compared with dairy cows at production level is related both to dry matter intake and digestibility at maintenance level: OMD(p) = 257 (+/-43) + 0.685 (+/-0.054) x OMD(m) (g/kg of dry matter) - 2.6 (+/-0.44) x dry matter intake (kg/d); adjusted residual mean square error = 8.4 g/kg. It was concluded that diet digestibility in dairy cows can be predicted accurately and precisely from digestibility estimated at maintenance intake in sheep by using regression models including animal and dietary factors.

A meta-analysis of feed digestion in dairy cows. 1. The effects of forage and concentrate factors on total diet digestibility.

A meta-analysis based on published experiments with lactating dairy cows was conducted to study the effects of dietary forage and concentrate factors on apparent total diet digestibility. A data set was collected that included a total of 497 dietary treatment means from 92 studies. The diets were based on grass silage or on legume or whole-crop cereal silages partly or completely substituted for grass silage. The silages were supplemented with concentrates given at a flat rate within a dietary comparison. For the statistical evaluation, the data were divided into 5 subsets to quantify silage (digestibility, 42 diets in 17 studies; fermentation characteristics, 108 diets in 39 studies) and concentrate (amount of supplementation, 142 diets in 59 studies; concentration of crude protein, 215 diets in 82 studies; carbohydrate composition, 66 diets in 23 studies) factors on total diet digestibility. The diet digestibility of dairy cows was determined by total fecal collection or by using acid-insoluble ash as an internal marker. Diet organic matter digestibility (OMD) at a maintenance level of feeding (OMD(m)) was estimated using sheep in vivo or corresponding in vitro digestibility values for the forage and reported ingredient and chemical composition values, with tabulated digestibility coefficients for the concentrate components of the diet. A mixed model regression analysis was used to detect the responses of different dietary factors on apparent total diet digestibility. Improved silage OMD(m) resulting from earlier harvest was translated into improved production-level OMD in cows (OMD(p)). The effects of silage fermentation characteristics on OMD(p) were quantitatively small, although sometimes significant. Concentrate supplementation improved total diet OMD(m), but this was not realized in lactating dairy cows because of linearly decreased neutral detergent fiber (NDF) digestibility as concentrate intake increased. Increasing the concentrate crude protein amount quadratically improved OMD(p) in cows, with the response being mostly due to improved NDF digestibility. Replacement of starchy concentrates with fibrous by-products slightly decreased OMD(p) but tended to improve NDF digestibility. The true digestibility of cell solubles (OM - NDF) estimated by the Lucas test both from all data and from the data subsets was not significantly different from 1.00, suggesting that responses in OMD(p) of dairy cows are mediated through changes in the concentration and digestibility of NDF.

Utilization and partition of dietary nitrogen in dairy cows fed grass silage-based diets.

Data from 207 production trials (998 treatment means) were used to study the effects of animal and dietary characteristics on the efficiency of N utilization for milk protein production, and on fecal N, urinary N, and total manure N output. The average efficiency of transferring dietary N to milk N (MNE; milk N/N intake) was 277 (SD = 36.0) g/kg. Nitrogen efficiency was poorly related to milk yield. Dietary concentrations of crude protein (CP) and protein balance in the rumen (PBV) were the best single predictors of MNE. Dietary CP concentration explained variation in MNE better than did N intake. Bivariate models with PBV or metabolizable protein (MP) explained the variation better than CP alone. The effects of protein feeding parameters on MNE were consistent among data subsets from studies investigating the effects of the amount and protein concentration of concentrate supplement, silage digestibility, silage fermentation quality, or substitution of grass silage with legume silage. The model with total dry matter and N intakes as independent variables explained fecal, urinary, and total manure N output more precisely than N intake alone. The model of fecal N output suggested that the true digestibility of dietary N was 0.91, and that metabolic and endogenous N was the major component in fecal N. The proportion of urine N in manure N was strongly related to dietary CP concentration. Including the concentration of dietary carbohydrates only slightly improved the models, indicating that the most effective strategy to improve MNE and to decrease N losses in manure, especially in urine, is to avoid feeding diets with excessively high CP concentration and especially excess ruminally degradable CP.

Relationships between silage fermentation characteristics and milk production parameters: analyses of literature data

Abstract Data from published production studies in lactating dairy cows were used to estimate relationships between silage fermentation characteristics and milk production parameters. The study used data from 47 experiments including 234 observations (treatment means). Within each experiment the silages were harvested at the same time from the same sward but using various additives. When factorial designs were used, silage data within each treatment (subexperiment) were recorded separately. Relationships between production parameters and silage fermentation parameters were analysed using mixed model regression analyses; with subexperiment within experiment as a random factor. Yields of milk, energy corrected milk (ECM), milk fat and protein decreased with increasing extent of in-silo fermentation. The effects were more profound for ECM than milk yield, because both milk fat and protein concentrations decreased ( P R 2 value between ME intake and ECM yield was 0.74 indicating that the effects on ECM yield were mainly derived from increased silage intake.

Evaluation of concentrate factors affecting silage intake of dairy cows: a development of the relative total diet intake index

The aim of this work was to develop an index describing the relative intake of the total diet by dairy cows, and hence the ability to predict intake responses to changes in both forage and concentrate variables. An evaluation of concentrate factors affecting silage dry matter (DM) intake of dairy cows was conducted based on dietary treatment means from milk production experiments. The data were divided into four subsets according to concentrate treatments used within the experiments: the amount of concentrate supplementation (n = 217), protein supplementation (n = 336), carbohydrate composition (n = 114) and fat concentration of the concentrate (n = 29). The data were subjected to mixed-model regression analysis. Increased concentrate DM intake (CDMI) decreased silage DM intake (SDMI) quadratically. The substitution rate (substitution of silage DM for concentrate DM) increased with improved silage intake potential. SDMI increased quadratically with concentrate protein intake, the response being negatively related to the effective protein degradability (EPD) of concentrates. Replacement of starchy concentrate ingredients with fibrous supplements had a small positive effect on silage intake, whereas increased concentrate fat concentration slightly decreased SDMI. The outcome of concentrate factors influencing total DM intake (TDMI) was used to create a relative CDMI index as follows: CDMI index = 100 + 10 × [(CDMI - 0.1629 × CDMI - 0.01882 × CDMI2 - 5.49) + ((0.9474 × CCPI - 0.4965 × CCPI2) - 2.017 × (CEPD - 0.74)) + 0.00225 × (CNDF - 250) - 0.0103 × (40 - Cfat) - 0.00058 × (CDMI - 8.0) × (SDMI index - 100)], where CDMI = concentrate DM intake (kg/day), CCPI = supplementary concentrate CP intake (kg/day; CP>170 g/kg DM), CEPD = concentrate EPD (g/g), CNDF = concentrate NDF concentration (g/kg DM), Cfat = concentrate fat concentration (g/kg DM) and SDMI index is the relative intake potential of silage (Huhtanen, Rinne and Nousiainen 2007. Animal 1, 758-770). TDMI index was calculated as SDMI index + CDMI index - 100 to describe the relative intake potential of the total diet. For the whole data set (n = 943), one TDMI index unit was equivalent to 0.095 kg/day DM intake, i.e. close to the default value of 0.100 kg. The CDMI index explained proportionally 0.88 of the variation in TDMI within a study with a 0.27 kg/day residual mean-square error (n = 616). The corresponding values for the TDMI index were 0.81 and 0.37 kg/day (n = 943), respectively. The residual mean-square errors in cross-validation were marginally higher. The developed TDMI index can be used to estimate the intake responses to diet changes. It provides an improved basis for practical dairy cow ration formulation and economic evaluation.

Effects of silage soluble nitrogen components on metabolizable protein concentration: a meta-analysis of dairy cow production experiments.

A meta-analysis based on 253 treatment means from 80 dairy cow production experiments was conducted to estimate the effects of the silage water-soluble N components on milk production, milk urea N concentration, and the efficiency of N utilization in milk production. The original experiments were conducted to study forage treatments (e.g., digestibility, fermentation quality, or wilting). Both the level and composition of concentrates were fixed within an experiment. Silage soluble N (g/kg of N) was divided into ammonia N and soluble nonammonia N, which was determined without the use of protein precipitants; that is, soluble nonammonia N as defined here encompassed proteins, peptides, and free AA. Metabolizable protein was calculated as AA absorbed from the small intestine by using constant values for ruminal protein degradability and intestinal digestibility of undegraded protein. Metabolizable energy and protein intakes were used as independent variables in regression models investigating the effects of soluble N components on energy-corrected milk and milk protein yields. A mixed regression model was used to account for between-experiment variations; that is, the response of fixed factors was studied within experiments. Silage soluble N components did not affect the energy-corrected milk yield when used in bivariate models with metabolizable energy intake. Solubility of silage N had a negative effect on milk protein yield when included in the model with metabolizable protein. However, this effect was almost completely related to ammonia N, whereas the effect of soluble nonammonia N was nonsignificant and negligible. The effects of soluble N components on milk urea N concentration and efficiency of N utilization in milk production were consistent with milk production responses. A lack of milk production responses to silage soluble nonammonia N suggested that the partition of silage N into soluble and insoluble N (excluding ammonia N) did not markedly influence silage metabolizable protein concentration. Analysis of silage N solubility has limited value in practical feed evaluation, and silage metabolizable protein concentration can be estimated with reasonable accuracy by using constant values for ruminal protein degradability and intestinal digestion of undegraded feed protein.

Integration of the effects of animal and dietary factors on total dry matter intake of dairy cows fed silage-based diets

An empirical regression model for the prediction of total dry matter intake (DMI) of dairy cows was developed and compared with four published intake models. The model was constructed to include both animal and dietary factors, which are known to affect DMI. For model development, a data set based on individual cow data from 10 change-over and four continuous milk production studies was collected (n = 1554). Relevant animal (live weight (LW), days in milk (DIM), parity and breed) and dietary (total and concentrate DMI, concentrate composition, forage digestibility and fermentation quality) data were collected. The model factors were limited to those that are available before the diets are fed to animals, that is, standardized energy corrected milk (sECM) yield, LW, DIM and diet quality (total diet DMI index (TDMI index)). As observed ECM yield is a function of both the production potential of the cow and diet quality, ECM yield standardized for DIM, TDMI index and metabolizable protein concentration was used in modelling. In the individual data set, correlation coefficients between sECM and TDMI index or DIM were much weaker (0.16 and 0.03) than corresponding coefficients with observed ECM (0.65 and 0.46), respectively. The model was constructed with a mixed model regression analysis using cow within trial as a random factor. The following mixed model was estimated for DMI prediction: DMI (kg DM/day) = -2.9 (±0.56)+0.258 (±0.011) × sECM (kg/day) + 0.0148 (±0.0009) × LW (kg) -0.0175 (±0.001) × DIM -5.85 (±0.41) × exp (-0.03 × DIM) + 0.09 (±0.002) × TDMI index. The mixed DMI model was evaluated with a treatment mean data set (207 studies, 992 diets), and the following relationship was found: Observed DMI (kg DM/day) = -0.10 (±0.33) + 1.004 (±0.019) × Predicted DMI (kg DM/day) with an adjusted residual mean square error of 0.362 kg/day. Evaluation of the residuals did not result in a significant mean bias or linear slope bias, and random error accounted for proportionally >0.99 of the error. In conclusion, the DMI model developed is considered robust because of low mean prediction error, accurate and precise validation, and numerically small differences in the parameter values of model variables when estimated with mixed or simple regression models. The Cornell Net Carbohydrate and Protein System was the most accurate of the four other published DMI models evaluated using individual or treatment mean data, but in most cases mean and linear slope biases were relatively high, and, interestingly, there were large differences in both mean and linear slope biases between the two data sets.

Effects of silage protein degradability and fermentation acids on metabolizable protein concentration: A meta-analysis of dairy cow production experiments

A meta-analysis was conducted using data from dairy cow production studies to evaluate silage metabolizable protein (MP) concentrations. The data consisted of 397 treatment means in 130 comparisons, in which the effects of silage factors (e.g., date of harvest, wilting, silage additives) were investigated. Within a comparison, a fixed amount of the same concentrate was fed. A prerequisite of data to be included in the analysis was that silage dry matter (DM), crude protein (CP), ammonia N, lactic acid (LA), and total acid (TA) concentrations and digestibility were determined. A smaller data set (n = 248) comprised studies in which silage water-soluble N concentration was also analyzed. The supply of MP was estimated as amino acids absorbed from the small intestine using a model with constant values for ruminal effective protein degradability (EPD) and intestinal digestibility of rumen undegraded protein. Microbial protein was calculated on the basis of digestible carbohydrates and rumen degradable protein (RDP). Alternative models were used to estimate microbial protein formation, assuming the energy values of RDP and TA to be equivalent to 1.00, 0.75, 0.50, 0.25, and 0 times that of digestible carbohydrates. Because EPD values are seldom determined in production trials, they were derived using empirical models that estimate them from other feed components. The goodness of fit of models was compared on the basis of root mean squared error (RMSE) of milk protein yield (MPY) predicted from MP supply (adjusted for random study effect) and Akaikes information criterion. Metabolizable protein supply calculated from basal assumptions predicted MPY precisely within a study (RMSE = 16.2 g/d). Variable contribution of RDP to the energy supply for microbial synthesis influenced the precision of MPY prediction very little, but RMSE for MPY increased markedly when the energy supply of rumen microbes was corrected for TA concentration. Using predicted rather than constant EPD values also increased RMSE of MPY prediction. These observations do not mean that the supply of MP from undegraded feed protein is constant. However, it suggests that our current methods overestimate the range in EPD values and that the techniques have so many inherent technical problems that they can mask the true differences between the feeds. Including new elements in feed protein evaluation models may not improve the precision of production response predictions unless the consequent effects on the supply of other nutrients are taken into account.